mcp-ai-image-generator
Related Servers
Alternatives to mcp-ai-image-generator
No user-submitted related servers found.
Related Servers
- AlicenseAqualityCmaintenanceEnables AI image generation, editing, and upscaling via Google Gemini and Imagen models, supporting dynamic model switching and multiple MCP-compatible clients.12MIT
- AlicenseAqualityAmaintenanceEnables AI image and video generation using Midjourney through the AceDataCloud API. It supports comprehensive features including image creation, transformation, blending, editing, and video generation directly within MCP-compatible clients.16261 PyPI9MIT
- AlicenseNot gradedqualityDmaintenanceEnables AI-powered image and video generation using Higgsfield AI models through MCP-compatible clients like Claude Desktop and Perplexity.252 npmMIT
- AlicenseBqualityDmaintenanceEnables AI image generation via MCP protocol, supporting dozens of models, customizable parameters, and multiple resolutions.37 npmISC
- AlicenseAqualityCmaintenanceEnables AI photo generation, editing, and video creation from MCP-compatible clients like Claude Desktop, Cursor, and Windsurf.89 npmMIT
- AlicenseBqualityDmaintenanceMCP server for generating and editing images using OpenAI, and creating videos using OpenAI Sora and Google Veo. Enables fetching media from URLs or disk with smart output placement.1418 npm9MIT
TDQS
Scored across 12 tools
Most tools target a distinct action or provider, but pairs like generate_image/generate_openai_image and edit_image/continue_editing could be confused without reading descriptions closely. The configure_* tools are also similar in name though their purposes differ clearly.
The set mostly follows an imperative verb_noun pattern in lowercase snake_case. Minor inconsistencies exist: list_history vs list_video_history is asymmetric, generate_image omits the provider while generate_openai_image includes it, and continue_editing uses a gerund instead of a noun object.
12 tools is a well-scoped count for a media generation server covering Gemini and OpenAI image/video generation, editing, history, configuration, and status. Each tool has a reasonable purpose and the count is not bloated or too thin.
Core workflows are covered: image generation/editing, video generation, history listing, configuration, authentication, and status. Minor gaps include no explicit OpenAI image editing, no per-provider model selection beyond the Gemini default, and no retrieval of past media by ID.